🌟S3T Playbook: Validating AI use cases

Avoid false starts and unrealistic expectations by using this framework to validate your AI use cases.

8 overlooked questions can determine whether a GenAI (or other AI) use case is actionable or not.

In the dynamic world of Gen AI, the ability to identifying legitimate and actionable use cases is becoming new crucial skillset for leaders. This is especially important for change leaders who naturally want to find ways to harness emerging technology for good.

Unfortunately it's not always easy to figure out exactly where and how an emerging technology like AI can be used. Today's overhyped expectations complicate matters further, creating a "why-can't-we-just-do-something" level of desperation among senior leaders.

If you've actually delivered AI solutions that had real world impact, you know the trial and error that it took to get there. Beneficial AI solutions are dependent on relevant, harmless data - which is not always easy to access.

I've been fortunate to be part of teams that delivered highly impactful AI models for healthcare, and there's nothing like getting feedback from patients and healthcare workers about how your solution helped them in a positive way. At the same time, I'd love to help others avoid some of the trial and error we had to go through in order to find the use cases that were actually impactful.

This guide offers a clear pathway to determine if your Gen AI project is set for success.

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